Runtime comparison
llama.cpp vs MLX LM
llama.cpp is a MIT-licensed runtime for Linux · macOS · Windows running on CUDA · Metal · CPU · Vulkan · ROCm; MLX LM is MIT-licensed for macOS on Metal. MLX LM rates easier to set up (4/5 vs 3/5 in our sourced ratings). Pick llama.cpp for serving many requests at once; pick MLX LM for maximum control over how the model runs.
| Spec | llama.cpp | MLX LM |
|---|---|---|
| License | MIT | MIT |
| Operating systems | Linux · macOS · Windows | macOS |
| GPU backends | CUDA · Metal · CPU · Vulkan · ROCm | Metal |
| Install | source / binary | pip |
| Ease of use | 3/5 | 4/5 |
| Quant formats | gguf | mlx |
| Engine | ggml | mlx |
| GitHub stars | 119,748 | 6,236 |
| Latest version | b9935 | v0.31.3 |
| Graphical app (GUI) | No | No |
| Server mode | Yes | Yes |
| OpenAI-compatible API | Yes | Yes |
| CPU offload | Yes | No |
| Multi-GPU | Yes | No |
| Speculative decoding | Yes | No |
| LoRA support | Yes | Yes |
| KV-cache quantization | Yes | Yes |
Which should you use?
llama.cpp
Best for serving many requests at once. Command line and server, runs on CUDA · Metal · CPU · Vulkan · ROCm.
Full llama.cpp guide →MLX LM
Best for maximum control over how the model runs. Command line and server, runs on Metal.
Full MLX LM guide →Neither runtime changes whether a model fits — that is your memory and quantization. Check your hardware first, then pick the runtime.
Sources: llama.cpp github.com/ggml-org/llama.cpp (as of 2026-07-11); MLX LM github.com/ml-explore/mlx-lm (as of 2026-07-08).